Effects of geodemographic profiles of drivers on their injury severity from traffic crashes using multilevel mixed-effects ordered logit model
2016-02-04T13:23:54Z (GMT) by
The purpose of this paper is to examine various geodemographic factors on the levels of driver injury severity using a statistical model. A driver’s geodemographic profile with respect to the involvement in a traffic crash consists of variables from multiple hierarchical levels such as drivers who are nested within crashes and crashes that are clustered within areas. A geodemographic profile of a driver therefore contains factors such as age, gender, residence of driver, social deprivation, and the distance from home to crash locations (at the driver-level); land-use patterns of crash location, casualties per crash and vehicles involved in the crash (at the crash- level); and vehicles per 1,000 population and population density (at the area-level). This implies that driver-level observations are correlated rather than independent as assumed in many injury severity modelling. In order to capture within-group and between-group correlations among observations a multilevel mixed-effects ordered logit model has been employed in this research. Mixed-effects allows some variables to vary by observations (i.e. random parameters). The analysis is based on UK national traffic crash data between 2009 to 2011 consisting of 271,654 drivers from 217,523 traffic crashes occurring across 27,773 different census areas. Data on area deprivation, Census, and land-use patterns were collected from multiple sources and integrated using a GIS framework. The results indicate that the severity of injuries sustained by urban drivers involved in crashes increases if they travel to rural areas; the level of driver injury severity also increases if traffic crashes occur in areas with high car ownership per capita; and drivers from more disadvantaged areas would sustain, if all else are equal, more severe injuries. The findings from this study would be useful to the Department for Transport and Local Authorities in formulating safety policies aimed at enhancing driver education, training and licensing programmes.